An Analysis on the Causes of Breast Cancer in Women Using Fuzzy Soft Covering Based Rough Sets and its Applications
Anjan Mukherjee, Somen Debnath · Annals of Pure and Applied Mathematics · 2018
Breast cancer normally occurs in women and most of it begin in the ducts that carry milk to the nipple.It is the second leading cause of cancer death in women.It causes abnormal cell growth in the breast and to spread other parts of the body.These cells form a tumor called malignant (cancerous).There are many risk factors which can increase the chance of developing breast cancer.Being a woman, getting older and genetic changes are the major risk factors for breast cancer.But it is not yet known exactly how some of these risk factors cause cells to cancerous.Imaging tests such as mammograms, ultrasound, MRI etc used to detect the breast disease.The modern researchers and technological advancements attempted to determine the cause and prevention of breast cancer in an effective manner with least number of attributes.Biopsy is the only sure way to diagnosis breast cancer.But the diagnosis is lengthy process with multiple and multilevel attribute analysis in certain cases.In order to improve the accuracy of diagnosis with limited attributes, in this paper fuzzy soft covering based rough sets are used and form an algorithm to reduce the number of attributes using equivalence relation.In this article, we investigate a data of 50 patients from different sources to find the patient/s with high breast cancer risk by using fuzzy soft covering based rough sets with the help of experts.